Gaussian processes (GPs) generalize the concept of a Gaussian distribution over discrete random variables to the idea of a Gaussian distribution over continuous functions [1]}.
GPs are particularly useful in uncertainty quantification due to their ability to simultaneously track the evolution of the mean and the covariance of a distribution.
